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interested candidate can drop your cv to 734 885 9771 Project Role : Data Platform Engineer Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NA Minimum 3 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As a Data Platform Engineer, you will assist with the data platform blueprint and design, encompassing the relevant data platform components. Your typical day will involve collaborating with Integration Architects and Data Architects to ensure cohesive integration between systems and data models, while also engaging in discussions to enhance the overall data architecture strategy. Job Title: Generative AI Engineer Job Description: We are seeking a Generative AI Engineer with 3.5+ years of experience to work with cutting-edge AI technologies, including RAG (Retrieval-Augmented Generation), Agentic AI, and transformer-based architectures, along with robust Python programming skills, to design, implement, and optimize AI-driven data solutions. AI Powered Tech Talent Roles & Responsibilities: Design and implement AI-powered data pipelines leveraging RAG models and transformers for advanced knowledge retrieval and generation tasks. Utilize LangChain, LangGraph, and other frameworks to build and integrate intelligent workflows and conversational agents. Develop Agentic AI solutions to create autonomous, goal-driven agents that interact with dynamic environments and data. Optimize data storage, processing, and retrieval techniques for large-scale AI platforms. Engineer prompt structures for optimized performance in generative AI tasks, including natural language processing (NLP) and multimodal applications. Ensure robust data privacy and security measures are in place for all AI-driven systems. Continuously monitor, troubleshoot, and enhance AI system performance. Collaborate with cross-functional teams (e.g., Data Scientists, Engineers) to integrate generative AI models into real-world data solutions. .